Computer-aided diagnosis in chest radiology.
Digital radiography offers several important advantages over conventional systems, including abilities for image manipulation, transmission, and storage. In the long term, however, the unique ability to apply artificial intelligence techniques for automated detection and quantitation of disease may have an even greater impact on radiologic practice. Although CAD is still in its infancy, the results of several recent studies clearly indicate a major potential for the future. The concept of using computers to analyze medical images is not new, but recent advances in computer technology together with progress in implementing practical digital radiography systems have stimulated research efforts in this exciting field. Several facets of CAD are presently being developed at the University of Chicago and elsewhere for application in chest radiology as well as in mammography and vascular imaging. To date, investigators have focused on a limited number of subjects that have been, by their nature, particularly suitable for computer analysis. There is no aspect of radiologic diagnosis that could not potentially benefit from this approach, however. The ultimate goal of these endeavors is to provide a system for comprehensive automated image analysis, the results of which could be accepted or modified at the discretion of the radiologist.
MacMahon
H
H
Department of Radiology, University of Chicago, Illinois 60637.
Doi
K
K
Chan
H P
HP
Giger
M L
ML
Katsuragawa
S
S
Nakamori
N
N
D001941:Breast Diseases / Q000000981:diagnostic imaging*; D003937:Diagnosis, Differential; D005260:Female; D006331:Heart Diseases / Q000000981:diagnostic imaging*; D006801:Humans; D007087:Illinois; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008171:Lung Diseases / Q000000981:diagnostic imaging*; D008327:Mammography / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*